MLOps Engineer

Job Title: MLOps Engineer

Location: On-site, 5 days per week

Total Compensation: Up to £200,000

We are seeking an experienced MLOps Engineer to join a forward-thinking trading organisation. This is an exciting opportunity to design and implement the infrastructure that powers advanced machine learning workflows in a production trading environment.

Key Responsibilities:

• Feature Store & Data Lake: Build scalable infrastructure for time-series feature storage, retrieval, and versioning optimised for ML workloads.
• MLOps Pipelines: Design end-to-end workflows for data ingestion, feature engineering, model training, backtesting, and deployment.
• Data Ingestion Layer: Connect raw data streams into structured, queryable formats (Parquet/Delta Lake).
• Production Serving: Deploy feature computation and model inference with appropriate latency characteristics.
• Integration: Collaborate with existing data capture and execution systems to ensure seamless operations.
• CI/CD Pipeline: Implement and maintain robust continuous integration and deployment pipelines for ML models.

Requirements:

• Strong experience in building and maintaining MLOps pipelines.
• Hands-on experience with feature stores, data lakes, and time-series data.
• Proficiency with modern data formats like Parquet and Delta Lake.
• Familiarity with production ML model deployment and latency optimisation.
• Experience integrating ML workflows with existing data and execution systems.
• Strong understanding of CI/CD practices in ML contexts.

Why This Role:

• Work in a cutting-edge, data-driven trading environment.
• Collaborate with a highly skilled team of engineers and data scientists.
• Opportunity to make a direct impact on ML infrastructure and trading performance.
• Competitive total compensation of up to £200,000.